Generative AI courses can help you learn how models create text, images, and other outputs using patterns learned from data. You can build skills in prompt design, model evaluation, and understanding how generative systems behave across tasks. Many courses introduce tools such as Python libraries, APIs, or model interfaces that support experimenting with generation and applying core concepts.

Skills you'll gain: Prompt Engineering, AI Orchestration, AI Workflows, Model Context Protocol, LangChain, Retrieval-Augmented Generation, Agentic Workflows, Tool Calling, LangGraph, LLM Application, Agentic systems, Multimodal Prompts, Generative AI, Generative AI Agents, Vector Databases, Generative Model Architectures, OpenAI API, Embeddings, Responsible AI, Software Development
Advanced · Professional Certificate · 3 - 6 Months

Duke University
Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Cloud Deployment, Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Hugging Face, Responsible AI, Data Manipulation, Exploratory Data Analysis, Containerization, DevOps, Cloud Computing, Python Programming, Machine Learning, GitHub, Big Data, Data Management, Data Analysis
Advanced · Specialization · 3 - 6 Months

Skills you'll gain: Prompt Engineering, Prompt Patterns, ChatGPT, Generative AI, Large Language Modeling, Responsible AI, AI Personalization, Mobile Development, AI Security, Data Ethics, Anthropic Claude, Artificial Intelligence, LLM Application, Software Testing, Apple iOS, AI Product Strategy, Software Development, Machine Learning Methods, Real Time Data, Artificial Intelligence and Machine Learning (AI/ML)
Advanced · Specialization · 1 - 3 Months

Google Cloud
Skills you'll gain: Model Deployment, Convolutional Neural Networks, Google Cloud Platform, Natural Language Processing, Tensorflow, MLOps (Machine Learning Operations), Reinforcement Learning, Transfer Learning, Computer Vision, Systems Design, Machine Learning Methods, Applied Machine Learning, Image Analysis, AI Personalization, Cloud Deployment, Recurrent Neural Networks (RNNs), Hybrid Cloud Computing, Systems Architecture, Performance Tuning, Embeddings
Advanced · Specialization · 3 - 6 Months

L&T EduTech
Skills you'll gain: Oil and Gas, Petroleum Industry, Hazard Analysis, Safety Standards, Environmental Resource Management, Energy and Utilities, Environmental Regulations, Environment Health And Safety, Big Data, Plant Operations and Management, Waste Minimization, Process Engineering, Chemical Engineering, Risk Analysis, Environmental Engineering, Failure Mode And Effects Analysis, Data Management, Pump Stations, Data Processing, Electric Power Systems
Advanced · Specialization · 3 - 6 Months

Google Cloud
Skills you'll gain: Large Language Modeling, Natural Language Processing, Generative Model Architectures, Transfer Learning, Embeddings
Advanced · Course · 1 - 4 Weeks

Skills you'll gain: Retrieval-Augmented Generation, OpenAI API, Generative AI, Large Language Modeling, Generative Adversarial Networks (GANs), ChatGPT, Generative AI Agents, Hugging Face, Artificial Intelligence and Machine Learning (AI/ML), Autoencoders, Applied Machine Learning, Prompt Engineering, Application Programming Interface (API), Transfer Learning, Machine Learning Algorithms, Data Preprocessing, Model Evaluation
Advanced · Course · 1 - 3 Months

Skills you'll gain: Feature Engineering, Model Deployment, Data Visualization, Data Ethics, Exploratory Data Analysis, Model Evaluation, Unsupervised Learning, Data Presentation, Tensorflow, Dimensionality Reduction, MLOps (Machine Learning Operations), Probability Distribution, Apache Spark, Statistical Hypothesis Testing, Supervised Learning, Data Pipelines, Design Thinking, Data Science, Machine Learning, Python Programming
Advanced · Specialization · 3 - 6 Months

Skills you'll gain: Object Oriented Programming (OOP), Data Structures, Python Programming, NumPy, Pandas (Python Package), Data Analysis, Scripting, Data Manipulation, Data Visualization, Algorithms, Debugging
Advanced · Course · 1 - 3 Months
University of Illinois Urbana-Champaign
Skills you'll gain: Deep Learning, Convolutional Neural Networks, Health Informatics, Autoencoders, Recurrent Neural Networks (RNNs), Image Analysis, Embeddings, Health Information Management, Machine Learning, Applied Machine Learning, Health Care, Model Deployment, Generative Adversarial Networks (GANs), Artificial Neural Networks, Healthcare Project Management, Supervised Learning, Model Evaluation, Machine Learning Methods, Graph Theory, Big Data
Advanced · Specialization · 1 - 3 Months

Skills you'll gain: Retrieval-Augmented Generation, Embeddings, Google Gemini, Vector Databases, Generative AI, Google Cloud Platform
Advanced · Course · 1 - 4 Weeks

University of Michigan
Skills you'll gain: Unsupervised Learning, Data Mining, Social Network Analysis, ChatGPT, Embeddings, Bayesian Network, Machine Learning Methods, Data Science, Supervised Learning, Generative AI, Machine Learning, Anomaly Detection, Data Preprocessing, Data Analysis, Recurrent Neural Networks (RNNs), Data Manipulation, Python Programming, Exploratory Data Analysis, Machine Learning Algorithms, Classification Algorithms
Advanced · Specialization · 3 - 6 Months
Generative AI refers to a subset of artificial intelligence that focuses on creating new content, whether it be text, images, music, or other forms of media. This technology is important because it has the potential to revolutionize various industries by automating creative processes, enhancing productivity, and enabling personalized experiences. As businesses increasingly adopt generative AI, understanding its capabilities and applications becomes crucial for anyone looking to stay relevant in the job market.‎
Careers in generative AI are diverse and growing rapidly. You can explore roles such as AI Engineer, Data Scientist, Machine Learning Engineer, and Software Developer, among others. Additionally, positions like AI Product Manager and Generative AI Consultant are emerging as organizations seek professionals who can effectively integrate this technology into their operations. The demand for skilled individuals in this field is expected to continue rising, making it a promising area for career development.‎
To succeed in generative AI, you should develop a strong foundation in programming languages such as Python or Java, as well as a solid understanding of machine learning concepts. Familiarity with AI frameworks and tools, such as TensorFlow or PyTorch, is also beneficial. Additionally, skills in data analysis, natural language processing, and creative thinking will enhance your ability to work with generative AI technologies effectively.‎
There are several excellent online courses available for learning about generative AI. For instance, the AWS Generative AI Applications Professional Certificate provides practical insights into applying generative AI in real-world scenarios. Another option is the IBM Generative AI Engineering Professional Certificate, which focuses on engineering aspects. These courses can help you build a solid understanding of generative AI principles and applications.‎
Yes. You can start learning generative AI on Coursera for free in two ways:
If you want to keep learning, earn a certificate in generative AI, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎
To learn generative AI, start by identifying your learning goals and the specific areas of interest within the field. Enroll in online courses that match your objectives, such as those focusing on programming, machine learning, or specific applications of generative AI. Engage with hands-on projects to apply what you learn, and consider joining online communities or forums to connect with others in the field. Consistent practice and exploration will help you build confidence and expertise.‎
Generative AI courses typically cover a range of topics, including the fundamentals of machine learning, neural networks, and natural language processing. You may also learn about specific generative models, such as GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders). Additionally, courses often explore practical applications, ethical considerations, and the integration of generative AI into various industries.‎
For training and upskilling employees, courses like the Generative AI for Software Development Skill Certificate and the Microsoft 365 with Generative AI Professional Certificate are excellent choices. These programs focus on practical skills and applications, making them suitable for organizations looking to enhance their workforce's capabilities in generative AI.‎